The goal of this postdoctoral fellowship is to facilitate the candidate's development as a leader in transplantation outcomes research, with a focus on perioperative cardiovascular (CV) risk assessment. Building on her background in internal medicine, transplant hepatology, and clinical investigation, the candidate proposes to develop additional skills during the award period through (1) coursework designed to expand her methodological skills; (2) interaction with a multidisciplinary team of sponsors and collaborators, including those in cardiovascular epidemiology, risk assessment, transplantation outcomes, and health services research; and (3) a supervised research project. The overall objective of this project is to define and optimize a preoperative cardiovascular risk assessment model for orthotopic liver transplant (OLT) candidates through two primary specific aims: (1) To determine if a national liver transplant-specific Cardiovascular Risk Index (NOLT-CRI) improves the predictive utility of the commonly used revised cardiac risk index (RCRI) by (1.1) determining the discrimination (C-statistic) and calibration (Hosmer-Lemeshow statistic) of the RCRI as a model of 30-day CV events using secondary data analysis of a national database; and (1.2) comparing the clinical performance of the NOLT-CRI to the RCRI in its ability to reclassify 30-day CV risk and to stratify 1- year survival across the continuum of predicted 30-day CV risk; (2) To determine whether additional variables are needed beyond those available within a national database in order to improve the predictive ability of these models by (2.1) determining the model discrimination and calibration of a locally-derived cardiac risk index (LOLT-CRI) using a center-specific database with more detailed clinical data than are currently available nationally; and (2.2) comparing the clinical performance of the LOLT-CRI to the national models in its ability to reclassify risk. This project will meet the mission of the National Institutes of Healthby identifying cardiovascular disease markers that are unique to the liver transplant candidate, which can then be used to improve pre- and post-transplant medical management in this growing patient population. The project, along with the chosen coursework and mentorship, will allow the candidate to become proficient at data management and statistical methodology. Near the end of the award period, the candidate plans to submit a career development award using the results of the project to develop a cardiovascular risk assessment treatment algorithm for use prior to liver transplantation.